Situational and Driver Characteristics Associated With Deervehicle Collisions in Southeastern Michigan

Deer-vehicle collisions (DVCs) create societal impacts throughout the range of white-tailed deer (Odocoileus virginanus). In Michigan reported DVCs increased by nearly 60% between 1992-2003, with current estimates at more than 65,000 DVCs per year and a mean of $2,300 vehicle damage. To better understand where to direct education and information programs, we used Office of Highway Safety Planning (OHSP) data, 2001-2003, to profile driver characteristics and accident situations of DVCs in Washtenaw, Oakland, and Monroe Counties in Michigan. Each county varies in intensity of land use, human and deer densities, and available deer habitat. Deer density in Washtenaw, Oakland, and Monroe Counties was 49.5, 21.9 and 8.9 per mi2, respectively, and the annual rate of DVCs in these counties was 5.3, 2.6 and 1.8 per 1,000 licensed drivers. Drivers are at particular risk of being involved in DVCs between 6pm- 6am, which includes dawn and dusk commuting hours, and night. Single lane roads and roads with higher posted speed limits provided greater risk to drivers of involvement in a DVC. Middle-aged drivers, particularly males, were at increased risk deer-related collisions. Results from this study will be combined with survey research to determine how best to educate drivers about risk factors that make occurrence of a DVC more likely.

Deer-Vehicle Crash Patterns Across Ecoregions in Michigan

Deer-vehicle collisions (DVCs) impact the economic and social well being of humans. We examined large-scale patterns behind DVCs across 3 ecoregions: Southern Lower Peninsula (SLP), Northern Lower Peninsula (NLP), and Upper Peninsula (UP) in Michigan. A 3 component conceptual model of DVCs with drivers, deer, and a landscape was the framework of analysis. The conceptual model was parameterized into a parsimonious mathematical model. The dependent variable was DVCs by county by ecoregion and the independent variables were percent forest cover, percent crop cover, mean annual vehicle miles traveled (VMT), and mean deer density index (DDI) by county. A discriminant function analysis of the 4 independent variables by counties by ecoregion indicated low misclassification, and provided support to the groupings by ecoregions. The global model and all sub-models were run for the 3 ecoregions and evaluated using information-theoretic approaches. Adjusted R2 values for the global model increased substantially from the SLP (0.21) to the NLP (0.54) to the UP (0.72). VMT and DDI were important variables across all 3 ecoregions. Percent crop cover played an important role in DVCs in the SLP and UP. The scale at which causal factors of DVCs operate appear to be finer in southern Michigan than in northern Michigan. Reduction of DVCs will likely occur only through a reduction in deer density, a reduction in traffic volume, or in modification of sitespecific factors, such as driver behavior, sight distance, highway features, or speed limits.